Difference between revisions of "DSC180F20W10"
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=Final Replication Checkpoint= | =Final Replication Checkpoint= | ||
− | + | The goal of the final project is to apply the Grad-CAM algorithm to the COCO dataset. | |
− | * | + | |
+ | ==Report== | ||
+ | |||
+ | Write a 3-6 pages long report on your final replication project. Include at least the following components: | ||
+ | |||
+ | * A title for your report | ||
+ | * Your team members' names | ||
+ | * Summarize your replication result | ||
+ | ** Include at least six images with heatmaps: three with correct predictions and three with incorrect predictions. | ||
+ | * Discuss shortcomings of your approach | ||
+ | * List possible improvements | ||
+ | * Conclusions: summarize what you learned from the project | ||
+ | |||
+ | ==Code== | ||
+ | |||
+ | * Develop functional Grad-CAM code which uses the COCO data set. | ||
+ | * Develop code that generates an analysis and figures for results. | ||
+ | * You can [https://github.com/jacobgil/pytorch-grad-cam use this code as a basis]. |
Latest revision as of 22:51, 13 December 2020
Final Replication Checkpoint
The goal of the final project is to apply the Grad-CAM algorithm to the COCO dataset.
Report
Write a 3-6 pages long report on your final replication project. Include at least the following components:
- A title for your report
- Your team members' names
- Summarize your replication result
- Include at least six images with heatmaps: three with correct predictions and three with incorrect predictions.
- Discuss shortcomings of your approach
- List possible improvements
- Conclusions: summarize what you learned from the project
Code
- Develop functional Grad-CAM code which uses the COCO data set.
- Develop code that generates an analysis and figures for results.
- You can use this code as a basis.